Today, machines (also referred to herein as “assets”) are ubiquitous in many industries. From locomotives that transfer cargo across countries to farming equipment that harvest crops, assets play an important role in everyday life.
Because of the increasing role that assets play, it is also becoming increasingly desirable to monitor and analyze assets in operation. To facilitate this, some have developed mechanisms to monitor asset attributes and detect abnormal conditions at an asset. For instance, one approach for monitoring assets generally involves various sensors and/or actuators distributed throughout an asset that monitor the operating conditions of the asset and provide signals reflecting the asset's operation to an on-asset computer. As one representative example, if the asset is a locomotive, the sensors and/or actuators may monitor parameters such as temperatures, pressures, fluid levels, voltages, and/or speeds, among other examples. If the signals output by one or more of the sensors and/or actuators reach certain values, the on-asset computer may then generate an abnormal condition indicator, such as a “fault code,” which is an indication that an abnormal condition has occurred within the asset. The on-asset computer may also be configured to monitor for, detect, and generate data indicating other events that may occur at the asset, such as asset shutdowns, restarts, etc.
The on-asset computer may also be configured to send data reflecting the attributes of the asset, including operating data such as signal data, abnormal-condition indicators, and/or asset event indicators, to a remote location for further analysis.
For instance, an organization that is interested in monitoring and analyzing assets in operation may deploy an asset data platform that is configured to receive and analyze various types of asset-related data. For example, the asset data platform may be configured to receive and analyze data indicating asset attributes, such as asset identifiers, asset operating data, asset configuration data, asset location data, etc. As another example, the data-analysis platform may be configured to receive and analyze asset maintenance data, such as data regarding inspections, servicing, and/or repairs. As yet another example, the data-analysis platform may be configured to receive and analyze external data that relates to asset operation, such as weather data, traffic data, or the like. The data-analysis platform may be configured to receive and analyze various other types of asset-related data as well.
Further, the asset data platform may receive this asset-related data from various different sources. As one example, the data-analysis platform may receive asset-related data from the assets themselves. As another example, the asset data platform may receive asset-related data from some other platform or system (e.g., an organization's existing platform) that previously received and/or generated asset-related data. As yet another example, the asset data platform may receive asset-related data from an external data source, such as an asset maintenance data repository, a traffic data provider, and/or a weather data provider for instance. The asset data platform may receive asset-related data from various other sources as well.